Non-tenure-track teaching faculty are becoming more important to doctoral departments to help them meet their educational goals and responsibilities, particularly in response to the current enrollments surge. In the Generation CS report (available at https://turing.cra.org/data/Generation-CS/), 65% of doctoral departments reported in fall 2015 that they had increased the number of teaching faculty on continuing appointments in response to increased enrollments, and an additional 16% were considering it. Similarly, between fall 2006 and fall 2016, the proportion of Taulbee Survey respondents reporting at least one full-time non-tenure-track teaching faculty member increased from 81% to 87% and, more notably, the median number of such teaching faculty at the departments reporting nonzero counts rose from 3 to 6.
Computing Research News
Published: August 2017, Issue: Vol. 29/No.7, Download as PDF
Archive of articles published in the August 2017, Vol. 29/No.7 issue.
The 2016 Taulbee Survey report, published in the May 2017 issue of CRN, did not include the results of a component that was introduced in the most recent survey–namely, bachelor’s enrollment data from specific courses in the curriculum. This component was introduced as a result of what was learned in the CRA Enrollment Report (see https://turing.cra.org/data/generation-cs). Unfortunately, we were unable to compile the data in time to feature the results in the May issue.
In the 2015 Taulbee report published in the May 2016 CRN, there were errors in the teaching load values presented in Table Prof1. Of particular import, the median values (the best comparison of typical teaching loads) for US CS Private, US CE, and US Information groups in the original report were higher than they should have been. Means also differ. Below is a corrected version of this table.
On Tuesday, July 11, the CRA Government Affairs Office welcomed the 2017 class of Eben Tisdale Fellows to the CRA Washington, DC office. These fellows, all of whom are undergraduates at universities and colleges across the United States, spent the summer at high-tech companies, firms, or trade associations in Washington, learning the intricacies of technology policy. Additionally, they took two class credits at George Mason University, and attended briefings at the U.S. Capitol, Department of State, World Bank, Federal Reserve, and other institutions. The fellows visited the office to attend a presentation by Brian Mosley, CRA’s Office of Government Affairs policy analyst, that covered the policy concerns and issues the association works on and influences at the federal level.
Just about every day we learn about a new application of cognitive computing. From predicting schizophrenia to analyzing Wimbledon fan experiences, cognitive computing and artificial intelligence have arrived and are making a measurable difference in our daily lives. But with all the excitement around real-world applications of this powerful technology, it is easy to forget that the Cognitive Era, as we call it at IBM, is still in its infancy. And there is a tremendous amount of work yet to be done. Collaborating with leading minds around the world is the key to fulfilling the true potential of cognitive computing. And that’s why IBM formed the Cognitive Horizons Network (CHN), a network of the world’s leading universities committed to working with IBM to accelerate the development of core technologies needed to advance the promise of cognitive computing.
I study how data and people interact. For more than a decade, I have been studying how to help humans access and manage information. While there is a lot of good work on human-computer interaction and on data visualization, much less work exists on “human-data interaction.” Why can anyone use Google to get information of interest while it is so difficult to get useful information from a structured database? The difference lies in the specificity of the request. A web search engine receives your request and tries to guess your intention. You know that it has a limited understanding of your need, and are happy to have it get you into “the zone,” from where you can explore for yourself. On the other hand, a traditional database query engine can give you complete answers to complex questions but requires that you precisely specify your query. If you make a small mistake, you are out of luck. Wouldn’t it be helpful to devise database query mechanisms that you can actually use and get reasonable results from even if you don’t ask it totally correctly? Complementarily, can the system help you ask a better question in the first place? Similar concerns also apply to the creation of a database, and helping users manage their data.
We found most undergraduate computing students believe computing careers afford ample opportunity to be in a position of influence and serve humanity. However, students believe computing careers afford relatively less opportunity to spend time with family. These findings suggest computing careers may be unattractive to groups of students who place strong value on family.
CCC welcomes new Council members and leadership for 2017-2018.
The following blog was written by CCC Vice Chair Mark D. Hill, with contributions from Sarita Adve and Alvin Lebeck. As readers of the Computing Community Consortium (CCC) blog know, CCC seeks to promote information technology research by exposing and developing synergies among researchers, research beneficiaries, and research funders. CCC does this through visioning activities, white papers, […]
The Computing Community Consortium (CCC) recently sponsored a workshop at the 2017 Robotics Science and Systems Conference called Material Robotics (MaRo).
Over the past few months we have been releasing blogs about the collective research agenda for intelligent infrastructure. This blog highlights an intelligent infrastructure paper called Intelligent Infrastructure for Smart Agriculture: An Integrated Food, Energy and Water System.